Integration: Madison Logic Intent Enrichment (via Universal Connector) Follow

Overview

Integrating your campaigns with Madison Logic intent data helps identify which companies are actively researching topics related to your offerings. This enables smarter lead prioritisation, more personalised outreach based on real buyer behaviour, and ultimately stronger campaign results.

In this guide, we’ll walk through setting up a Universal Connector job to query data from Madison Logic's intent enrichment service, match and append it to your existing leads, and then deliver the enriched leads to your marketing platforms.

Please note:

• Get in touch with your Convertr Customer Success Manager to see if the Madison Logic solution is available for your account.

Configuring Universal Connector to Enrich Leads with Madison Logic Intent API

1. Go to the Processr > Quality Assurance tab of your campaign.
2. Click the "Add" button to add a new job.
3. Select "Universal Connector" from the dropdown.
4. Configure sections as provided below.

API Endpoint

ApiUrl: https://public-gateway-api.proda.madisonlogic.com/api/v1/leads/enrichment
Method: post
Verify_ssl_peer: Yes
Send_as_json: Yes

Headers

Authorization: Bearer ##token##

OAuth

URL: https://public-gateway-api.proda.madisonlogic.com/api/v1/okta/token?clientId=<Your client ID>&technicalPartnerName=convertr
Access_token_key: accessToken
Method: post

Mapping

campaignId: <Internal campaign ID provided by Madison Logic>|int
email: email

ResultMapping

This will map Madison Logic intent data to lead fields ml_topic_1, ml_category_1, ml_score_1, etc.

ml_topic_1: topics.0.topic_name
ml_category_1: topics.0.category_name
ml_score_1: topics.0.mli_score
ml_topic_2: topics.0.topic_name
ml_category_2: topics.0.category_name
ml_score_2: topics.0.mli_score
ml_topic_3: topics.0.topic_name
ml_category_3: topics.0.category_name
ml_score_3: topics.0.mli_score

Please note: In this example, we have configured storing of the top three intent topics provided by Madison Logic intent API. However, Madison Logic provides up to ten top intent topics with their categories and scores that you can store against your leads.

ValidationConditions

Leave the default validation configuration (no validation) if you don't want to fail leads when Madison Logic API doesn't have any intent data for them.

Configuring Delivery of Enriched Lead Data

We can integrate Madison Logic intent data to the customer backend platforms along with the other lead data.

1. Go to Processr > Integration
2. Click the 'Add' button to add new integration job or edit the existing integration job
3. Add fields appended by Madison Logic enrichment to the Mapping section of the integration job configuration

This will send mlTopic1, mlCategory1, mlScore1, etc. fields as part of the integration:

mlTopic1: job_data[1173][core.data.0.ml_topic_1]
mlCategory1: job_data[1173][core.data.0.ml_category_1]
mlScore1: job_data[1173][core.data.0.ml_score_1]
mlTopic2: job_data[1173][core.data.0.ml_topic_2]
mlCategory2: job_data[1173][core.data.0.ml_category_2]
mlScore2: job_data[1173][core.data.0.ml_score_2]
mlTopic3: job_data[1173][core.data.0.ml_topic_3]
mlCategory3: job_data[1173][core.data.0.ml_category_3]
mlScore3: job_data[1173][core.data.0.ml_score_3]

Please note: You may need to configure your backend platform to correctly accept these fields.